Change Detection Using Change Vector Analysis from Landsat TM Images in Wuhan

被引：24

作者：

Song Xiaolu ^{[1
]}

Cheng Bo ^{[2
]}

机构：

[1] Chinese Acad Sci, Grad Univ, Ctr Earth Observat & Digital Earth, Beijing 100864, Peoples R China

[2] Digital Earth Chinese Acad Sci, Ctr Earth Observat, Beijing, Peoples R China

来源：

2011 2ND INTERNATIONAL CONFERENCE ON CHALLENGES IN ENVIRONMENTAL SCIENCE AND COMPUTER ENGINEERING (CESCE 2011), VOL 11, PT A | 2011年 / 11卷

基金：

中国国家自然科学基金;

关键词：

Change detection; Change vector analysis; Dichotomy; Threshold search; Direction cosine vector space;

D O I：

10.1016/j.proenv.2011.12.037

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Spectral Change Vector Analysis (CVA) is based on multi-temporal images. In this paper, a dichotomy search which can be used on detecting changes in the threshold vector is adopted. Meanwhile, a supervised classification technique is used in the direction cosine space with the type of central point in the initial assay vector remote sensing images. Results are discussed in the last part of this paper, which show that CVA can extract change information effectively in our study area of Wuhan city. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the Intelligent Information Technology Application Research Association.

引用

页码：238 / 244

页数：7

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